Description
The files included are part of the CriticalMaaS research on ride-hailing and on-demand transport services. In this study, passengers' perception of waiting time variability was analysed.
Respondents were presented with 32 hypothetical scenarios with immediate feedback on the performance of their selected alternatives. This feedback information was then incorporated into their decision-making for the following scenario.
Information on the data and model can be found in the README file and the python script.
Respondents were presented with 32 hypothetical scenarios with immediate feedback on the performance of their selected alternatives. This feedback information was then incorporated into their decision-making for the following scenario.
Information on the data and model can be found in the README file and the python script.
| Date made available | 21 Mar 2023 |
|---|---|
| Publisher | TU Delft - 4TU.ResearchData |
| Date of data production | 2023 |
| Geographical coverage | Netherlands |
Research output
- 1 Article
-
An instance-based learning approach for evaluating the perception of ride-hailing waiting time variability
Geržinič, N., Cats, O., van Oort, N., Hoogendoorn-Lanser, S., Bierlaire, M. & Hoogendoorn, S., 2023, In: Travel Behaviour and Society. 33, 11 p., 100616.Research output: Contribution to journal › Article › Scientific › peer-review
Open AccessFile5 Link opens in a new tab Citations (Scopus)109 Downloads (Pure)
Cite this
- DataSetCite